Choosing Reinsurance Treaties is one of the most difficult business tasks in the insurance business. Just a tiny tweak towards optimal reinsurance can save millions.
There are several considerations when it comes to Reinsurance Optimization. So it should be part of broader company reinsurance strategy answering these questions:
- For what types of policies should the company increase sales efforts next year? Which ones are the most profitable?
- How will the claims distributions develop in future (having in mind the next year’s sales plan)? On which scale will this impacts the profitablity?
- How much reinsurance funds do we need?
- We should choose our risk preferences. Should we go for the maximum profit or should we increase the company security?
- And last but not least – which types of reinsurance treaties will be optimal?
So even if we know the answers to all above we still have some decisions to make. If we make combination of proportional reinsurance and non-proportional reinsurance treaties – where should we set the layer limits?
Should we take quota share up until $1M and then an excess of loss from $1M up to $100M?
Why should we set the reinsurance layer to be on $1M exactly?
In most cases it is more profitable if the layer limits are not set arbitrarily but rather on complex calculations. How to find this magical number for the layer limits? It is not an industry secret that even big insurance companies can have trouble with this.
The actuarial mathematicians have to build mathematical models for predicting the future. So the first task on their hand is to predict the number of claims and volume of claims. Then this allows the reinsurance analysts within the insurance companies to negotiate with several reinsurance companies.
They usually use statistical data such as number and type of policies sold, number of claims, volume of claims in the past. They also plan together with the marketing and sales department the future sales plan.
The future predictions are based on the mathematical model of the claims distribution and probabilistic predictions. And the insurance company understands it’s needs in terms of reinsurance treaties.
Choosing the right combination of reinsurance treaties from a variety of treaties and multiple reinsurance companies can be a very difficult task. The reinsurance department managers should care about reinsurers ratings but also their willingness for effective cooperation.
But even if we exclude these human factors, we have a lot to analyze. The reinsurance optimization involves building probabilistic models that compare the different outcomes for all the combinations of all feasible treaties.
Choosing optimal treaty
Every class of insurance can be covered by a variety of layers. It can be Quota share treaty up until a limit from one company, then surplus layer from another and XL treaty on top of it from a third company.
The best treaty combination for the insurance company is the one which ensures highest profit at high probability of surviving. Based on the strategy of the insurance company the optimal reinsurance treaty can be one with the highest protection for a certain amount of ceded premium.
The optimal reinsurance strategy can be the one with the lowest amount of premium ceded to a certain level of reinsurance protection.
To help out in this messy business we recommend the reinsurance software – Optimalreinsurance.com which promises to guide the reinsurance managers within the insurance companies and help them out during this tough decision.
OptimalReinsurance.com builds the mathematical models and defines the best treaties based on the portfolio and they allow companies to find the best combination of treaties.
A small enhancement in the Reinsurance Strategy can bring millions even to small companies. Optimizing Reinsurance is one of the best ways to increase the Insurance company profitability.
Insurtech entrepreneur. Founder and CEO of systemsforenterprie.com
Experienced Business Developer with a demonstrated history in the insurance software industry. Serial architect of great teams and amazing team dynamics. Generalist with strong skills in: management, business planning, project management, behavioral economics, marketing strategy, training and public speaking. Master focused in Product Life-cycle Management. Digital transformation evangelist.